From c95102a0bd0d0554edad57b8dc027d72ae05094e Mon Sep 17 00:00:00 2001
From: agentson <agentson@localhost>
Date: Tue, 10 Feb 2026 04:25:37 +0900
Subject: [PATCH] feat: DailyScorecard model for per-market performance review
 (issue #90)

- Add DailyScorecard dataclass with market-scoped fields
- Fields: date, market, decisions, pnl, win_rate, scenario_match_rate, lessons, cross_market_note
- Export from src/evolution/__init__.py

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---
 src/evolution/__init__.py  |  2 +
 src/evolution/scorecard.py | 25 ++++++++++++
 tests/test_scorecard.py    | 81 ++++++++++++++++++++++++++++++++++++++
 3 files changed, 108 insertions(+)
 create mode 100644 src/evolution/scorecard.py
 create mode 100644 tests/test_scorecard.py

diff --git a/src/evolution/__init__.py b/src/evolution/__init__.py
index 0267d8c..3346a61 100644
--- a/src/evolution/__init__.py
+++ b/src/evolution/__init__.py
@@ -7,6 +7,7 @@ from src.evolution.performance_tracker import (
     PerformanceTracker,
     StrategyMetrics,
 )
+from src.evolution.scorecard import DailyScorecard
 
 __all__ = [
     "EvolutionOptimizer",
@@ -16,4 +17,5 @@ __all__ = [
     "PerformanceTracker",
     "PerformanceDashboard",
     "StrategyMetrics",
+    "DailyScorecard",
 ]
diff --git a/src/evolution/scorecard.py b/src/evolution/scorecard.py
new file mode 100644
index 0000000..06d0b2b
--- /dev/null
+++ b/src/evolution/scorecard.py
@@ -0,0 +1,25 @@
+"""Daily scorecard model for end-of-day performance review."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+
+
+@dataclass
+class DailyScorecard:
+    """Structured daily performance snapshot for a single market."""
+
+    date: str
+    market: str
+    total_decisions: int
+    buys: int
+    sells: int
+    holds: int
+    total_pnl: float
+    win_rate: float
+    avg_confidence: float
+    scenario_match_rate: float
+    top_winners: list[str] = field(default_factory=list)
+    top_losers: list[str] = field(default_factory=list)
+    lessons: list[str] = field(default_factory=list)
+    cross_market_note: str = ""
diff --git a/tests/test_scorecard.py b/tests/test_scorecard.py
new file mode 100644
index 0000000..ff2563f
--- /dev/null
+++ b/tests/test_scorecard.py
@@ -0,0 +1,81 @@
+"""Tests for DailyScorecard model."""
+
+from __future__ import annotations
+
+from src.evolution.scorecard import DailyScorecard
+
+
+def test_scorecard_initialization() -> None:
+    scorecard = DailyScorecard(
+        date="2026-02-08",
+        market="KR",
+        total_decisions=10,
+        buys=3,
+        sells=2,
+        holds=5,
+        total_pnl=1234.5,
+        win_rate=60.0,
+        avg_confidence=78.5,
+        scenario_match_rate=70.0,
+        top_winners=["005930", "000660"],
+        top_losers=["035420"],
+        lessons=["Avoid chasing breakouts"],
+        cross_market_note="US volatility spillover",
+    )
+
+    assert scorecard.market == "KR"
+    assert scorecard.total_decisions == 10
+    assert scorecard.total_pnl == 1234.5
+    assert scorecard.top_winners == ["005930", "000660"]
+    assert scorecard.lessons == ["Avoid chasing breakouts"]
+    assert scorecard.cross_market_note == "US volatility spillover"
+
+
+def test_scorecard_defaults() -> None:
+    scorecard = DailyScorecard(
+        date="2026-02-08",
+        market="US",
+        total_decisions=0,
+        buys=0,
+        sells=0,
+        holds=0,
+        total_pnl=0.0,
+        win_rate=0.0,
+        avg_confidence=0.0,
+        scenario_match_rate=0.0,
+    )
+
+    assert scorecard.top_winners == []
+    assert scorecard.top_losers == []
+    assert scorecard.lessons == []
+    assert scorecard.cross_market_note == ""
+
+
+def test_scorecard_list_isolation() -> None:
+    a = DailyScorecard(
+        date="2026-02-08",
+        market="KR",
+        total_decisions=1,
+        buys=1,
+        sells=0,
+        holds=0,
+        total_pnl=10.0,
+        win_rate=100.0,
+        avg_confidence=90.0,
+        scenario_match_rate=100.0,
+    )
+    b = DailyScorecard(
+        date="2026-02-08",
+        market="US",
+        total_decisions=1,
+        buys=0,
+        sells=1,
+        holds=0,
+        total_pnl=-5.0,
+        win_rate=0.0,
+        avg_confidence=60.0,
+        scenario_match_rate=50.0,
+    )
+
+    a.top_winners.append("005930")
+    assert b.top_winners == []